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Given a subset K of the unit Euclidean sphere, we estimate the minimal number m = m(K) of hyperplanes that generate a uniform tessellation of K, in the sense that the fraction of the hyperplanes separating any pair x, y in K is nearly…

Probability · Mathematics 2013-09-27 Yaniv Plan , Roman Vershynin

Re-Pair is an efficient grammar compressor that operates by recursively replacing high-frequency character pairs with new grammar symbols. The most space-efficient linear-time algorithm computing Re-Pair uses $(1+\epsilon)n+\sqrt n$ words…

Data Structures and Algorithms · Computer Science 2017-04-28 Philip Bille , Inge Li Gørtz , Nicola Prezza

We present three new approximation algorithms with improved constant ratios for selecting $n$ points in $n$ disks such that the minimum pairwise distance among the points is maximized. (1) A very simple $O(n\log n)$-time algorithm with…

Computational Geometry · Computer Science 2015-03-13 Adrian Dumitrescu , Minghui Jiang

We study the following range searching problem in high-dimensional Euclidean spaces: given a finite set $P\subset \mathbb{R}^d$, where each $p\in P$ is assigned a weight $w_p$, and radius $r>0$, we need to preprocess $P$ into a data…

Computational Geometry · Computer Science 2026-03-13 Andreas Kalavas , Ioannis Psarros

Quantitative estimates related to the classical Borsuk problem of splitting set in Euclidean space into subsets of smaller diameter are considered. For a given $k$ there is a minimal diameter of subsets at which there exists a covering with…

Metric Geometry · Mathematics 2022-10-25 Alexander Tolmachev , Dmitry Protasov , Vsevolod Voronov

Given $x \in (\mathbb{R}_{\geq 0})^{\binom{[n]}{2}}$ recording pairwise distances, the METRIC VIOLATION DISTANCE (MVD) problem asks to compute the $\ell_0$ distance between $x$ and the metric cone; i.e., modify the minimum number of entries…

Data Structures and Algorithms · Computer Science 2022-08-31 Vincent Cohen-Addad , Chenglin Fan , Euiwoong Lee , Arnaud de Mesmay

LP-type problems such as the Minimum Enclosing Ball (MEB), Linear Support Vector Machine (SVM), Linear Programming (LP), and Semidefinite Programming (SDP) are fundamental combinatorial optimization problems, with many important…

Data Structures and Algorithms · Computer Science 2025-07-17 N. Efe Çekirge , William Gay , David P. Woodruff

We consider a bichromatic two-center problem for pairs of points. Given a set $S$ of $n$ pairs of points in the plane, for every pair, we want to assign a red color to one point and a blue color to the other, in such a way that the value…

Computational Geometry · Computer Science 2019-05-02 Haitao Wang , Jie Xue

We study the classic Euclidean Minimum Spanning Tree (MST) problem in the Massively Parallel Computation (MPC) model. Given a set $X \subset \mathbb{R}^d$ of $n$ points, the goal is to produce a spanning tree for $X$ with weight within a…

Data Structures and Algorithms · Computer Science 2023-08-02 Rajesh Jayaram , Vahab Mirrokni , Shyam Narayanan , Peilin Zhong

We provide a spectrum of new theoretical insights and practical results for finding a Minimum Dilation Triangulation (MDT), a natural geometric optimization problem of considerable previous attention: Given a set $P$ of $n$ points in the…

Computational Geometry · Computer Science 2025-02-26 Sándor P. Fekete , Phillip Keldenich , Michael Perk

The Erd\H os unit distance conjecture in the plane says that the number of pairs of points from a point set of size $n$ separated by a fixed (Euclidean) distance is $\leq C_{\epsilon} n^{1+\epsilon}$ for any $\epsilon>0$. The best known…

Classical Analysis and ODEs · Mathematics 2017-09-26 Alex Iosevich

We propose and examine the use of biphoton pairs, such as those created in parametric down conversion or four-wave mixing, to enhance the precision and the resolution of measuring optical displacements by position-sensitive detection. We…

Quantum Physics · Physics 2016-05-04 Kevin Lyons , Shengshi Pang , Paul G. Kwiat , Andrew N. Jordan

We derive lower bounds on the maximal rates for multiple packings in high-dimensional Euclidean spaces. Multiple packing is a natural generalization of the sphere packing problem. For any $ N>0 $ and $ L\in\mathbb{Z}_{\ge2} $, a multiple…

Metric Geometry · Mathematics 2022-11-10 Yihan Zhang , Shashank Vatedka

Let $P$ be a set of $n$ points in $\mathbb{R}^d$, in general position. We remove all of them one by one, in each step erasing one vertex of the convex hull of the current remaining set. Let $g_d(P)$ denote the number of different removal…

Combinatorics · Mathematics 2024-11-15 Dániel Gábor Simon

We study the problem of $2$-dimensional orthogonal range counting with additive error. Given a set $P$ of $n$ points drawn from an $n\times n$ grid and an error parameter $\eps$, the goal is to build a data structure, such that for any…

Data Structures and Algorithms · Computer Science 2016-05-24 Zhewei Wei , Ke Yi

In this article, we consider the Euclidean dispersion problems. Let $P=\{p_{1}, p_{2}, \ldots, p_{n}\}$ be a set of $n$ points in $\mathbb{R}^2$. For each point $p \in P$ and $S \subseteq P$, we define $cost_{\gamma}(p,S)$ as the sum of…

Computational Geometry · Computer Science 2021-05-20 Pawan K. Mishra , Gautam K. Das

Tensors decompositions are a class of tools for analysing datasets of high dimensionality and variety in a natural manner, with the Canonical Polyadic Decomposition (CPD) being a main pillar. While the notion of CPD is closely intertwined…

Signal Processing · Electrical Eng. & Systems 2019-11-15 Giuseppe G. Calvi , Bruno Scalzo Dees , Danilo P. Mandic

In this paper, we investigate the approximability of two node deletion problems. Given a vertex weighted graph $G=(V,E)$ and a specified, or "distinguished" vertex $p \in V$, MDD(min) is the problem of finding a minimum weight vertex set $S…

Data Structures and Algorithms · Computer Science 2014-01-15 Sounaka Mishra , Ashwin Pananjady , N Safina Devi

Consider the length $L_{MM}^E$ of the minimum matching of N points in d-dimensional Euclidean space. Using numerical simulations and the finite size scaling law $< L_{MM}^E > = \beta_{MM}^E(d) N^{1-1/d}(1+A/N+... )$, we obtain precise…

Disordered Systems and Neural Networks · Physics 2009-10-30 Jacques Boutet de Monvel , Olivier C. Martin

The 2-Wasserstein distance (or RMS distance) is a useful measure of similarity between probability distributions that has exciting applications in machine learning. For discrete distributions, the problem of computing this distance can be…

Computational Geometry · Computer Science 2020-07-17 Nathaniel Lahn , Sharath Raghvendra